Skip to main content

 –

Creating models

Suggest edit Updated on March 11, 2021

In the Model creation step, you get sample models: one default regression model, one default decision tree model, and optionally by a benchmark model or models. During modeling, you can add more models and save them. A good practice is to create each type of model and compare their key characteristics.

  • In the Model creation step, check the following data:
    • To verify the predictive performance achieved by the model based on the development set, check the Development set column.
    • To verify the predictive performance achieved by the model based on the test set, check the Test set column.
    • To verify the predictive performance achieved by the model based on the validation set, check the Validation set column.
    • To verify the number of predictors used in the model, check the # Predictors column.
    • To verify the list of predictors in the model, check the Predictors column.
  • Creating a regression model

    Create a model that works well on linear data.

  • Creating a decision tree model

    Create a model that works well on mid-volume, highly non-linear data.

  • Creating a bivariate model

    Build a model with two predictors that have univariate performance.

  • Creating a genetic algorithm model

    Create a genetic algorithm model while you are building predictive models to generate highly predictive, non-linear models. A genetic algorithm solves optimization problems by creating a generation of possible solutions to the problem.

  • Computation models

    The process of model development allows you to create such default models as regression, decision tree, genetic algorithm, and bivariate.

Did you find this content helpful? YesNo

Have a question? Get answers now.

Visit the Collaboration Center to ask questions, engage in discussions, share ideas, and help others.

Ready to crush complexity?

Experience the benefits of Pega Community when you log in.

We'd prefer it if you saw us at our best.

Pega.com is not optimized for Internet Explorer. For the optimal experience, please use:

Close Deprecation Notice
Contact us